Search

In this paper we describe the development of the software module for an embedded system, which realizes Fast Frequency Hopping for a radio device. The module is designed using the SDL modelling language, then implemented in C++ language, targeting a custom board equipped with Vx Works operating system. The main focus of the paper is on a new object oriented library, called "SDL Framework" (SDL-F), that has been developed with the main objective of allowing fast mapping of SDL elements into native C++ objects. The paper describes the reasons which have lead to the development of SDL-F framework and presents its main features and performances.

GMSK is an efficient modulation technique for digital mobile communications. In this paper a simple solution to the modeling and simulation of GMSK systems impaired by fading channels and additive white Gaussian noise is given, and its effects on the channel characteristics are also considered. The modeling is based on the well-known linearized representation of phase-modulated signals. The analysis is not only useful for modeling and simulation purposes, but also gives a tool for the design of simple receivers.

This contribution considers the power control and signal-shaping problem for ad-hoc networks composed by multi-antenna non-cooperative terminals affected by spatially colored multiple-access interference (MAI). The multi-antenna interference channel is modeled as a non cooperative and strategic game. Furthermore iterative power control and signal shaping algorithms are presented to efficiently achieve the Nash equilibrium under best effort and "contracted QoS" policies.

The optimal transmitting and receiving filters are jointly designed for twisted-pair channels in presence of intersymbol interference (ISI), additive white Gaussian noise and crosstalk. As a design criterion the signal-to-noise ratio at the decision point is maximized under the zero-ISI constraint. The case of non-synchronous interfering data signals is considered, so that the crosstalk can be modeled as an additive colored Gaussian noise independent from the transmitted signal and a continuous-time analysis can be carried out. This makes the proposed solution valid for analog communication systems too. Some basic design parameters which optimize the transmission system are then easily computed, and the resulting performance is evaluated.

The analysis of bathymetry of seas, oceans and lakes is a very important activity, since it allows the study of morphology of the floor and also can aid the channel modeling if underwater communication must take place. A Sonar is usually the device used for accomplish this task. It is an acoustic radar, able to send pulses and analyze the reflections. Hence, in this work we derive the bathymetric map of a very shallow water reservoir by using a sonar system characterized by two separated devices, one transmitting and one receiving so allowing the signal detection also during signal transmission. This allows to consider very shallow depths, of the order of few meters, and the system proposed is also low cost. It requires a transmitter, a hydrophone and a software processing tool to offline estimating depth.

New methods for estimating the autocorrelation function (acf) of a complex Gaussian stationary process are presented. These methods are based on a general invariance property for the autocorrelation of a common class of the above processes. This property suggests estimation procedures based on magnitude hard limiting and phase quantization. The procedures are an extension of the relay estimator, currently employed for real processes. The computational cost and the general properties of the methods are discussed. In particular, some estimators especially suited for very simple implementations are considered. The performance of the complex hybrid sign estimator is evaluated and compared to that of the classical Direct estimator. The proposed methods are attractive for many applications in the field of digital signal processing.

The complementary aspects of spectrum estimation based on higher-order order statistics are considered. Higher-order analysis of stochastic array data is formalized in a general fashion through the introduction of the class of hybrid nonlinear (HNL) moments. HNL moments comprise, as a special case, slice cumulants and their mixtures. In this framework, the case of joint use of covariance and fourth-order slice cumulant is handled in a simple and direct way. Simulation results confirm the theoretical analysis. >

This paper presents a novel procedure, named Hierarchical Compressive Sampling Matching Pursuit (CoSaMP), for reconstruction of compressively sampled sparse signals whose coefficients are organized according to a nested structure. The Hierarchical CoSaMP is inspired by the CoSaMP algorithm, and it is based on a suitable hierarchical extension of the support over which the compressively sampled signal is reconstructed. We analytically demonstrate the convergence of the Hierarchical CoSaMP and show by numerical simulations that the Hierarchical CoSaMP outperforms state-of-the-art algorithms in terms of accuracy for a given number of measurements at a restrained computational complexity.

Underwater acoustic communications can be used for several applications. When the underwater link is related to a reservoir, applications can go from water monitoring, both in terms of pollution and physical characteristics, as for example, temperature. Another class of applications can be the remote control of small vehicles/vessels. Due to the limited depth, this kind of underwater acoustic connection suffers from delay spread and, in a wider sense, intersymbol and/or interpulse interference. In this work we analyze the problem of delay spread and test the performance in terms of BER for single link in a reservoir when 16-PPM is used according to Desert Star Systems LLC SAM-1 Modem. We propose also an adaptive detection scheme so as to reduce bit error rate. Last we compare the performance of the modem in the receive mode with a hybrid receiver characterized by hardware/software operations.

Starting from some general results about Hidden Markov Models (HMMs) recently appeared in literature (Baccarelli and Cusani, 1996; Elliott et al, 1995), low-complexity decision-delay constrained symbol-by-symbol maximum-likelihood detectors for data-transmission over noisy time-dispersive time-variant waveform channels with quantised demodulation are presented. The resulting equalisers are recursive and nonlinear, minimise the symbol error probability and their complexity grows only linearly (and not exponentially) with the value assumed by the decision-delay. A new family of Bhattacharyya-like upper bounds is also presented for the analytical evaluation of their performance.